Cutting-edge Omics Technology Innovations Empower Livestock and Poultry Biological Breeding

doi:10.13560/j.cnki.biotech.bull.1985.2024-0733

Abstract

Abstract:

The growth of the global population has led to an increase in the demand for livestock and poultry products, while climate change and environmental pressures pose challenges to the survival and production of livestock and poultry. The independently selected core livestock and poultry breeds in China is rather lack, and thus "biological breeding" has become a "national strategy" for the New Quality Productivity of Agriculture. Therefore, it is necessary to breed new livestock and poultry breeds with excellent traits and strong adaptability. The continuous development of omics and molecular biology technology has promoted the development and improvement of genomics, transcriptomics, epigenetics, three-dimensional genomics, metagenomics, and single-cell and other multi-omics technologies, and successfully combined and applied to genome-wide association analysis, marker-assisted selection, genome-wide selection and other livestock and poultry bio-breeding methods. With the innovation and development of cutting-edge genomics technologies, the potential molecular genetic mechanisms of livestock and poultry biomorphogenesis have also been realized to be resolved. In order to make better use of Genomic & Multi-omics Breeding techniques and concepts to help livestock and poultry biological breeding, this review summarizes the contents and characteristics of the main livestock and poultry biological trait formation and molecular breeding-related genomics technologies. It firstly describes the principles and applications of classical genomics technologies, which are mainly related to genomes, transcriptomes, proteomes, etc. Meanwhile, it also pointed out the limitations of these technologies, and introduced a series of new omics technologies, including three-dimensional (3D) genomics, gut microbiomics and single-cell omics. It also summarizes the application of the Genomic & Multi-omics Breeding concept in the analysis of economically important traits and molecular biological breeding of livestock and poultry and outlines the application scenarios and challenges of these genomics technologies. Finally, the review discusses the comprehensive application of multi-omics technology, and looks forward to the future development trend of genomics technology. It aims to provide new references for the research of important traits of livestock and poultry and the development of breeding field, and to promote the development of livestock and poultry breeding towards a more precise, efficient, and economical direction.

Key words: livestock and poultry, traits, omics technologies, genomes, three-dimensional genomes, metagenomes, biotechnological breeding

LI Chen-ying, KONG Da-shuai, LI Ruo-nan, ZHANG Yu-bo, YAN ping, LI Kui, KONG Si-yuan. Cutting-edge Omics Technology Innovations Empower Livestock and Poultry Biological Breeding[J]. Biotechnology Bulletin, 2025, 41(6): 71-86.

Figures/Tables 3

References 96

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分类 Classification	技术 Technology	关键流程 Process	优势和局限性 Advantages and limitations	应用场景 Applications	参考文献Reference
经典的组学技术 Classical omics techniques	Sanger sequencing	PCR扩增‒PCR纯化‒循环测序‒测序纯化‒毛细管电泳‒数据分析	优势：读取速度快、高精确度，成本相对很低局限：无法连续测序、测序长度受限制	基因突变检测、基因编辑、微生物鉴定与分型	［13］
	Next-generation sequencing	核酸提取‒文库制备‒上机测序‒数据分析	优势：通量高、速度快、测序成本低、敏感性高、所需样本量少局限：成本高、操作复杂、检测周期长	全基因组测序与全外显子测序、基因变异、基因分型等	［14］
	RNA-seq	总RNA提取‒rRNA去除‒双链合成‒末端修复‒接头连接‒文库扩增‒测序	优势：定量更准确、可重复性更高、检测范围更广、分析更可靠局限：限制其他RNA的读数以及其他RNA表达水平的准确性	基因表达量测量与差异表达分析、新转录本、剪接形式和基因的发现、非编码RNA研究、生物标志物发现等	［30］
	ChIP-seq	甲醛交联‒DNA片段化‒染色质免疫沉淀‒捕获DNA‒蛋白质复合物‒纯化DNA‒测序	优势：大量细胞起始量，挖掘转录因子、蛋白因子全基因组结合位点局限：该技术需要高度特异性抗体、甲醛固定可能是暂时的，甚至是非特异的，可能导致相邻的蛋白形成假阳性信号	转录因子（TF）结合位点和靶基因的全基因组鉴定、组蛋白修饰的全基因组检测、蛋白质- DNA互作研究	［36］
	微生物组16S rDNA测序	细菌基因组提取‒特异引物扩增16S rDNA序列‒纯化PCR产物‒测序获得16S rDNA序列	优势：具有良好的进化保守性、操作速度快、操作简单、成本低局限：可以鉴定到属水平，无法准确到所有物种或亚种水平	微生物群落的多样性、病原菌检测与鉴定、生态系统功能研究	［74］
	宏基因组二代鸟枪法测序 Shotgun sequencing	将DNA序列随机分解成许多小片段‒通过寻找重叠区域来重新组装序列	优势：速度快，简单易行，成本较低局限：会形成大量冗余序列，导致基因组信息的缺失	分析微生物群落的结构、环境微生物群落研究、功能基因发掘、医学诊断与研究、生态与环境保护	［76］
新兴的组学技术 Emerging omics technologies	三代单分子测序 Single-molecule sequencing	DNA片段化‒发夹连接‒获得文库‒文库测序	优势：可以直接进行 cDNA 分析、无需逆转录、测序速度极快局限：单读长错误率高增加测序成本	基因组测序、甲基化研究、突变鉴定	［15］
	CUT&Tag	提取细胞核‒抗体结合‒Tn5结合‒回收DNA‒PCR扩增‒文库测序	优势：背景噪声低、细胞起始量低、信噪比和重复性较好局限：细胞数量要求较高、实验耗时长、数据的重复性较差	蛋白质与DNA互作研究、鉴定转录因子在全基因组上的结合位点、超级增强子鉴定	［38］
	Hi-C	甲醛交联‒限制酶切‒末端补平‒邻近连接‒超声破碎‒biotin富集‒建库测序	优势：高通量测序、Hi-C可以展现出，整个染色体all-to-all的互作关系局限：实验成本高、数据噪声大、实验过程繁琐	研究染色体片段之间的相互作用、基因组组装、单体型图谱构建、辅助宏基因组组装、与其他数据进行联合分析、基因调控网络、表观遗传网络	［58］
	In situ Hi-C	交联‒酶切‒邻近连接‒超声破碎‒生物素下拉‒建库测序	优势：高效、方便、比对率高和低成本局限：暂无法进行单细胞水平	疾病相关基因定位、基因表达调控、识别染色体结构变异、基因组进化与比较基因组学、药物靶点发现	［59］
	In situ exo-Hi-C	交联‒酶切‒邻近连接‒线性DNA消除‒超声破碎‒ 生物素下拉‒建库测序	优势：高效、方便、噪声低、比对率高和低成本局限：暂无法进行单细胞水平	低细胞起始量、下机测序数据少，噪声低，需求有效互作得率高。畜禽发育机制解析，功能基因挖掘等农业、医学应用	［63］
	ChIA-PET	甲醛交联‒DNA片段化‒用特异性蛋白抗体富集DNA和蛋白复合物‒生物素下拉‒限制性内切酶消化‒去除蛋白质‒固定化PET序列‒上机测序	优势：高效、高分辨率、应用范围广泛局限：细胞起始量要求更高、操作相对复杂	基因转录调控、疾病发生机制、生长发育、基因组功能研究、药物研发等	［60-62］
	GutHi-C	微生物分离提纯‒交联裂解‒酶切‒末端补平‒纯化‒片段化‒接头连接‒文库扩增	优势：效率高，便于操作，成本低，数据优局限：如手动裂解破壁步骤需要熟手操作	广泛用于畜禽肠道微生物建库	［78］
高精度的组学技术 Highly accurate omics technology	scRNA-seq	细胞收集‒分选捕获单个细胞‒细胞裂解‒提取DNA‒合成cDNA‒扩增‒测序	优势：高分辨率、可探索未知的细胞类型局限：不同类型的细胞在解离效率上存在差异、对细胞悬液质量的高要求、技术复杂	单细胞分辨率揭示胚胎发育过程、基因表达的动态变化、微生物群落	［90］
	scATAC-seq	细胞收集‒分离单细胞‒裂解‒转座‒扩增酶切割‒扩增‒测序	优势：高通量、低成本、高分辨率局限：技术涉及多个步骤，对实验技术和数据分析要求较高、数据解读和结果分析具有挑战性、不同平台的实验方法和数据分析流程可能存在差异，影响结果的通用性和可比性	单细胞分辨率揭示胚胎发育过程、肿瘤生物学、免疫细胞的基因表达调控、细胞间互作	［88］
	snHi-C	细胞核分离‒交联‒酶切‒末端修复‒连接‒纯化‒建库‒测序	优势：分辨率较高、灵敏度高局限：成本高、实验复杂	单细胞分辨率揭示染色质三维结构、调控网络	［89］
	Dip-C	细胞分离裂解‒交联固定‒染色质片段化‒连接‒标记‒ 构建文库‒测序	优势：高分辨率、可以在单细胞水平上进行基因组三维结构的研究局限：成本高、实验复杂	单细胞分辨率揭示基因组三维结构的动态变化、染色质互作、调控网络	［89］
	scNanoHi-C	交联固定‒Tn5片段化‒连接-扩增-构建文库‒三代单分子Nanopore测序	优势：高阶连接子的效率更高、在单个细胞中检测到更多的接触、捕获更多的杂合SNP位点进行单倍型分析局限：Nanopore错误率高一些	单细胞分辨率揭示染色质高维结构、染色质高阶互作和调控网络	［90］
	MUSIC	分离细胞核‒标记同一细胞核中的所有RNA和片段化DNA‒将RNA和DNA接头连接到RNA和DNA片段上‒构建单个测序文库	优势：分辨率高、能够同时分析单个细胞核内的多重染色质相互作用、基因表达和RNA-染色质关联，提供丰富的单细胞多组学信息局限：成本相对较高	同时检测单细胞染色质三维结构和基因表达的动态变化、基因表达以及RNA-染色质关联的差异	［91］

分类 Classification	技术 Technology	关键流程 Process	优势和局限性 Advantages and limitations	应用场景 Applications	参考文献Reference
经典的组学技术 Classical omics techniques	Sanger sequencing	PCR扩增‒PCR纯化‒循环测序‒测序纯化‒毛细管电泳‒数据分析	优势：读取速度快、高精确度，成本相对很低局限：无法连续测序、测序长度受限制	基因突变检测、基因编辑、微生物鉴定与分型	［13］
	Next-generation sequencing	核酸提取‒文库制备‒上机测序‒数据分析	优势：通量高、速度快、测序成本低、敏感性高、所需样本量少局限：成本高、操作复杂、检测周期长	全基因组测序与全外显子测序、基因变异、基因分型等	［14］
	RNA-seq	总RNA提取‒rRNA去除‒双链合成‒末端修复‒接头连接‒文库扩增‒测序	优势：定量更准确、可重复性更高、检测范围更广、分析更可靠局限：限制其他RNA的读数以及其他RNA表达水平的准确性	基因表达量测量与差异表达分析、新转录本、剪接形式和基因的发现、非编码RNA研究、生物标志物发现等	［30］
	ChIP-seq	甲醛交联‒DNA片段化‒染色质免疫沉淀‒捕获DNA‒蛋白质复合物‒纯化DNA‒测序	优势：大量细胞起始量，挖掘转录因子、蛋白因子全基因组结合位点局限：该技术需要高度特异性抗体、甲醛固定可能是暂时的，甚至是非特异的，可能导致相邻的蛋白形成假阳性信号	转录因子（TF）结合位点和靶基因的全基因组鉴定、组蛋白修饰的全基因组检测、蛋白质- DNA互作研究	［36］
	微生物组16S rDNA测序	细菌基因组提取‒特异引物扩增16S rDNA序列‒纯化PCR产物‒测序获得16S rDNA序列	优势：具有良好的进化保守性、操作速度快、操作简单、成本低局限：可以鉴定到属水平，无法准确到所有物种或亚种水平	微生物群落的多样性、病原菌检测与鉴定、生态系统功能研究	［74］
	宏基因组二代鸟枪法测序 Shotgun sequencing	将DNA序列随机分解成许多小片段‒通过寻找重叠区域来重新组装序列	优势：速度快，简单易行，成本较低局限：会形成大量冗余序列，导致基因组信息的缺失	分析微生物群落的结构、环境微生物群落研究、功能基因发掘、医学诊断与研究、生态与环境保护	［76］
新兴的组学技术 Emerging omics technologies	三代单分子测序 Single-molecule sequencing	DNA片段化‒发夹连接‒获得文库‒文库测序	优势：可以直接进行 cDNA 分析、无需逆转录、测序速度极快局限：单读长错误率高增加测序成本	基因组测序、甲基化研究、突变鉴定	［15］
	CUT&Tag	提取细胞核‒抗体结合‒Tn5结合‒回收DNA‒PCR扩增‒文库测序	优势：背景噪声低、细胞起始量低、信噪比和重复性较好局限：细胞数量要求较高、实验耗时长、数据的重复性较差	蛋白质与DNA互作研究、鉴定转录因子在全基因组上的结合位点、超级增强子鉴定	［38］
	Hi-C	甲醛交联‒限制酶切‒末端补平‒邻近连接‒超声破碎‒biotin富集‒建库测序	优势：高通量测序、Hi-C可以展现出，整个染色体all-to-all的互作关系局限：实验成本高、数据噪声大、实验过程繁琐	研究染色体片段之间的相互作用、基因组组装、单体型图谱构建、辅助宏基因组组装、与其他数据进行联合分析、基因调控网络、表观遗传网络	［58］
	In situ Hi-C	交联‒酶切‒邻近连接‒超声破碎‒生物素下拉‒建库测序	优势：高效、方便、比对率高和低成本局限：暂无法进行单细胞水平	疾病相关基因定位、基因表达调控、识别染色体结构变异、基因组进化与比较基因组学、药物靶点发现	［59］
	In situ exo-Hi-C	交联‒酶切‒邻近连接‒线性DNA消除‒超声破碎‒ 生物素下拉‒建库测序	优势：高效、方便、噪声低、比对率高和低成本局限：暂无法进行单细胞水平	低细胞起始量、下机测序数据少，噪声低，需求有效互作得率高。畜禽发育机制解析，功能基因挖掘等农业、医学应用	［63］
	ChIA-PET	甲醛交联‒DNA片段化‒用特异性蛋白抗体富集DNA和蛋白复合物‒生物素下拉‒限制性内切酶消化‒去除蛋白质‒固定化PET序列‒上机测序	优势：高效、高分辨率、应用范围广泛局限：细胞起始量要求更高、操作相对复杂	基因转录调控、疾病发生机制、生长发育、基因组功能研究、药物研发等	［60-62］
	GutHi-C	微生物分离提纯‒交联裂解‒酶切‒末端补平‒纯化‒片段化‒接头连接‒文库扩增	优势：效率高，便于操作，成本低，数据优局限：如手动裂解破壁步骤需要熟手操作	广泛用于畜禽肠道微生物建库	［78］
高精度的组学技术 Highly accurate omics technology	scRNA-seq	细胞收集‒分选捕获单个细胞‒细胞裂解‒提取DNA‒合成cDNA‒扩增‒测序	优势：高分辨率、可探索未知的细胞类型局限：不同类型的细胞在解离效率上存在差异、对细胞悬液质量的高要求、技术复杂	单细胞分辨率揭示胚胎发育过程、基因表达的动态变化、微生物群落	［90］
	scATAC-seq	细胞收集‒分离单细胞‒裂解‒转座‒扩增酶切割‒扩增‒测序	优势：高通量、低成本、高分辨率局限：技术涉及多个步骤，对实验技术和数据分析要求较高、数据解读和结果分析具有挑战性、不同平台的实验方法和数据分析流程可能存在差异，影响结果的通用性和可比性	单细胞分辨率揭示胚胎发育过程、肿瘤生物学、免疫细胞的基因表达调控、细胞间互作	［88］
	snHi-C	细胞核分离‒交联‒酶切‒末端修复‒连接‒纯化‒建库‒测序	优势：分辨率较高、灵敏度高局限：成本高、实验复杂	单细胞分辨率揭示染色质三维结构、调控网络	［89］
	Dip-C	细胞分离裂解‒交联固定‒染色质片段化‒连接‒标记‒ 构建文库‒测序	优势：高分辨率、可以在单细胞水平上进行基因组三维结构的研究局限：成本高、实验复杂	单细胞分辨率揭示基因组三维结构的动态变化、染色质互作、调控网络	［89］
	scNanoHi-C	交联固定‒Tn5片段化‒连接-扩增-构建文库‒三代单分子Nanopore测序	优势：高阶连接子的效率更高、在单个细胞中检测到更多的接触、捕获更多的杂合SNP位点进行单倍型分析局限：Nanopore错误率高一些	单细胞分辨率揭示染色质高维结构、染色质高阶互作和调控网络	［90］
	MUSIC	分离细胞核‒标记同一细胞核中的所有RNA和片段化DNA‒将RNA和DNA接头连接到RNA和DNA片段上‒构建单个测序文库	优势：分辨率高、能够同时分析单个细胞核内的多重染色质相互作用、基因表达和RNA-染色质关联，提供丰富的单细胞多组学信息局限：成本相对较高	同时检测单细胞染色质三维结构和基因表达的动态变化、基因表达以及RNA-染色质关联的差异	［91］

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